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Concrete measures: the rise of public housing and changes in young single motherhood in the U.S.

Abstract

Between 1950 and 1970, the number of public housing units in the United States grew nearly sixfold, and the percentage of births to unmarried women almost tripled. We provide the first estimates of the effect of public housing on single motherhood, using individual-level data to assess whether young women living near higher concentrations of public housing were more likely to have children out of wedlock. We find a strong and positive relationship between public housing and single motherhood for black high school dropouts. This link is larger when we use lagged measures of public housing, which suggests that exposure during childhood may be driving the result.

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Notes

  1. Female-headed households are more likely to have incomes below the poverty line (Garfinkel and McLanahan 1986) and have been linked with adverse child outcomes, such as lower educational attainment (Dawson 1991; McLanahan and Sandefur 1994), psychological problems (Aseltine 1996; Hetherington and Clingempeel 1992; Zill and Peterson 1986), and illicit activity (Flewelling and Bauman 1990).

  2. Currie and Yelowitz (2000) and Jacob (2004) assess the effects of public housing on children’s educational attainment; neither study finds evidence of adverse effects of public housing on educational attainment. Aliprantis and Hartley (2015) and Sandler (2017) find that the demolition of public housing projects in Chicago reduced crime in those neighborhoods and in the city as a whole. Yelowitz (2001) finds that increases in the size of public housing subsidies decrease labor force participation among female household heads. Chyn (2016) finds that children who were displaced due to project demolitions in Chicago in the 1990s moved into lower-poverty neighborhoods and were more likely to be employed and have higher earnings in adulthood.

  3. In 2015, approximately 90% of households with children living in public housing were headed by women (HUD 2015).

  4. Our sample period ends in 1970 for two reasons. First, while additional public housing units were built after 1970, the relative importance of the public housing program declined in the 1970s with the introduction of the Section 8 Housing Voucher program. The second reason is more practical: our unique public housing dataset ends in 1973.

  5. Between 1949 and 1970, the number of public housing units increased from 146,000 to 830,000. (These figures come from an unpublished table generously provided by Edgar Olsen that he received while working on the National Housing Policy Review in 1972–1973.)

  6. Construction started in 1934, and by 1937 the PWA had constructed approximately 22,000 units in 36 metropolitan areas (National Commission on Urban Problems 1969; Coulibaly et al. 1998).

  7. This statistic comes from an unpublished table generously provided by Edgar Olsen that he received while working on the National Housing Policy Review during 1972–1973.

  8. Housing authorities also conducted spot checks to ensure that extra tenants were not living in units (Stoloff 2004). The New York City Housing Authority usually excluded individuals with a “bad previous record as a housekeeper or parent” or a history of drug use or violent behavior (National Commission on Urban Problems 1969, 116). It was common for project managers and staff to inspect apartments to ensure that tenants were keeping their apartments clean. Tenants were fined for letting their children play on the grass or for not taking out the trash. In Chicago, tenants were also supposed to help with maintenance by cleaning stairwells or cutting the grass (Hunt 2009). In Cincinnati, tenants were given a handbook which forbade them from conducting business in their units and encouraged them to become friends with their neighbors and avoid gossiping (Fairbanks 1988).

  9. Changes in housing markets in the decades after World War II also affected the characteristics of prospective tenants interested in public housing. During this period, the housing shortage felt by many cities during the war declined, and the quality of the private housing stock increased. This decreased the demand for public housing by the working class, increasing the percentage of public housing units occupied by very low-income households (Hunt 2009; Vale 2007).

  10. Collins and Margo (2000) replicate Cutler and Glaeser’s analysis for earlier years and find that the positive relationships between segregation and both single motherhood and idleness do not appear until the 1970s.

  11. See Carter et al. (1998); Massey and Kanaiaupuni (1992); and Holloway et al. (1998).

  12. We use the 1950 1% sample, the 1970 1% met2 sample, and the 1960 5% sample.

  13. Minor changes to the boundaries in 1960 for these 15 MSAs do not affect our results. As a robustness check, we create alternative sets of 1960 boundaries for these MSAs using a set of “small” boundaries, in which we include only geographic units that lie completely inside our consistent 1950 and 1970 boundaries, and a set of “large” boundaries, in which we include all geographic units that lie at least partially inside our consistent 1950 and 1970 boundaries. Results using these alternative definitions are both very similar to the results reported in the paper. See the appendix for a detailed description of the construction of MSA boundaries.

  14. IPUMS has created rules (MOMRULE) to use information about an individual’s relationship to the head of the household and their relative position within the household to estimate the location of an individual’s mother in the household (MOMLOC) and to impute the NCHILD variable. For example, these rules include linking individuals who are listed as children of the head of the household to female household heads, and linking grandchildren of the household head to daughters of the household head (under certain conditions). See https://usa.ipums.org/usa-action/variables/MOMRULE#description_section. Because we received the 1960 5% sample from IPUMS before its official release, it did not yet contain their NCHILD variable, so we reconstructed it following their rules. See the appendix for details.

  15. Our results are not sensitive to this choice of age range. We find similar, if not larger, results for ages 19–25, 20–26, and 21–27. We report these estimates in the appendix.

  16. We have also estimated probit models of our preferred specification for all of the analyses presented in this paper. The probit results are very similar to the linear probability estimates.

  17. When we regress our high school graduate indicator on public housing intensity and individual- and MSA-level controls (similar to specifications 3 and 4), we find that a one percentage point increase in public housing intensity is associated with a 2–3 percentage point decrease in the likelihood of young black women graduating from high school in 1960 (although imprecisely estimated) and a 5 percentage point decrease in 1970 (statistically significant at the 5% level).

  18. The 1950 census did not report everyone’s educational attainment. Select questions were only “asked of persons on selected lines of the population schedule” (https://usa.ipums.org/usa/voliii/1950samp.shtml). We therefore do not know the education status of 76% of our 1950 sample. We include an additional bin in our regressions for individuals with unknown educational attainment.

  19. We have also implemented a placebo test to address the concern that public housing is correlated with time-varying unobservable MSA characteristics. It may be concerning if the change in public housing, our identifying variation, was correlated with long-term MSA trends as revealed by changes in MSA characteristics much earlier or later than the time period we study. We regress 1990–2000 changes in an MSA characteristic—such as single motherhood rates, marriage rates, or employment rates—on the 1950–1960 change in public housing prevalence and region fixed effects. We repeat this exercise using 1980–2000 changes in MSA characteristics and the 1950–1970 change in public housing prevalence. We run these regressions with and without population weights. Of 36 public housing coefficients, only one is statistically significant, and the point estimates are generally very small.

  20. We estimate specification 3 of Tables 3 and 4 using alternative age ranges for women between 18 and 29 years of age. Results are reported in appendix Tables A3 and A4. We find slightly larger effects for black high school dropouts (Tables 3 and A3) when using ages 19–25, 20–26, and 21–27 (point estimates of 0.018–0.020 compared to 0.015). When we allow for the effects to differ by year (Tables 4 and A4), we find similar coefficients for black high school dropouts in 1970 for these alternative age bins.

  21. Sinai and Waldfogel (2005) find that government-subsidized housing increased the 1990 housing stock. Each subsidized unit increased the total housing stock by approximately one third to one half of a unit, with larger effects in urban areas.

  22. We found that lags of 8–15 years yielded similar results.

  23. A potential concern is that the lagged public housing results among black high school dropouts in the 1950s may indicate that there are important differences between MSAs with and without public housing in 1940. To address this, we have allowed each public housing coefficient in Table 5 to differ based on whether the MSA had any public housing in 1940. (Of the 56 MSAs in our sample, only 24 had any public housing units in 1940.) We find that the coefficient on lagged public housing among black high school dropouts in 1970 is positive and statistically significant among both groups of MSAs.

  24. We use our estimated coefficients from specification 3 of Table 4. In 1970, we have three education bins: in high school (coefficients not reported), high school dropout, and high school graduate. We multiply the race- and education-specific public housing coefficients by the race-specific mean of public housing intensity in 1970 and take the weighted average within race. Public housing is predicted to increase black single motherhood by 0.25 percentage points, which is 4% of the observed 6.3 percentage point increase in black single motherhood. If we “zero out” the statistically insignificant negative coefficients for education groups other than high school dropouts, we find that public housing explains an increase in black single motherhood of 1.1 percentage points, or 17% of the observed increase in black single motherhood.

  25. Between 1990 and 2007, Chicago demolished, sold, or repurposed over 16,000 units of public housing, while Philadelphia and Atlanta both removed over 7000, New Orleans and Baltimore more than 5000, and Newark and Detroit more than 4000 (Goetz 2013). By 2010, Philadelphia and Baltimore had knocked down 21 public housing towers, and Chicago had demolished 79 (Fernandez 2010).

  26. https://usa.ipums.org/usa-action/variables/MOMRULE#description_section. IPUMS implements a couple of additional rules as well that are not described above. We implemented only the rules described here, as they captured the vast majority of mother‐child links.

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Acknowledgements

The authors thank the editor and anonymous referees of this journal for very helpful comments and suggestions. We also thank William J. Collins, Timothy Diette, Price Fishback, Art Goldsmith, Joseph Guse, Greg Hartman, Ed Olsen, Nick Sanders, and participants from Washington & Lee University, Virginia Military Institute, The College of William & Mary, and the Virginia Association of Economists and Southern Economic Association annual meetings. Carolyn Moehling graciously provided ADC/AFDC data. Lilly Grella, Margaret Hambleton, John Juneau II, Margaret Kallus, Charlotte Karp, Grant Przybyla, and Amanda Wahlers provided excellent research assistance.

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Correspondence to Katharine L. Shester.

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Appendix

Appendix

Additional details on the history of U.S. public housing

Public housing policy differed by city and over time, but some general themes can be identified. Two prominent commonalities were the location of projects within cities and the rapid deterioration of housing quality. Public housing construction frequently propagated racial residential segregation and severely restricted the educational and employment opportunities of tenants. Meanwhile, the declining quality of housing contributed to projects’ reputation as last-resort housing riddled with substandard living conditions and high crime rates.

Location of public housing projects

Following the Housing Act of 1937, local housing authorities and city councils, through “cooperation agreements,” determined the number and placement of public housing projects within cities. However, city councils and mayors commonly rejected sites proposed by housing authorities due to pressure from constituents who did not want public housing in their neighborhood. In 1949, Detroit’s new mayor vetoed eight of 12 proposed public housing sites within his first weeks in office (Sugrue 1996). In 1950, Baltimore City Council rejected sites proposed by the local housing authority after residents spoke out against public housing at a council meeting, and in 1951, the Los Angeles City Council did the same (Hunt 2009). By 1952, Chicago’s housing authority “had surrendered site selection power to city hall and the city council, letting them choose sites without debate” (Hunt 2009, 92). This was a common story for many other cities as well, including Washington, D.C. and Baltimore (Goetz 2013).

The influence of constituent opinion via city council and mayoral authority led to locational choices for public housing that commonly supported and strengthened racial residential segregation. This trend has been well documented in various major cities. For example, Chicago’s housing authority estimated similar costs for locating public housing in white and black neighborhoods and initially proposed sites in both. However, by the late 1940s, “the prospect of active opposition from owner-occupied sites made clearing white neighborhoods a time-consuming and politically perilous task” (Hunt 2009, 43). Opposition to public housing was so strong that in 1971 Alderman Frank Kuta said that he would rather go to jail than have public housing in his ward. In Atlanta, public housing construction was part of a full-scale redevelopment plan that included encouraging black migration to the south and west of downtown (Silver and Moeser 1995). Charlotte also located projects miles from the center of downtown, on the far northwest edge of an established black neighborhood “in accordance with [its] vision of [a] sorted-out city” (Hanchett 1998, 238). Other prominent examples include Detroit (Sugrue 1996), Cincinnati (Fairbanks 1988), Philadelphia (Bauman 1987), Memphis, and Richmond (Hanchett 1998).

These location choices also had important implications for the employment and educational opportunities of public housing residents. In many cities, public housing was placed far from employment opportunities and in places with poor access to public transportation, which made it difficult for tenants to find work. In Detroit, authorities located public housing in the inner city while jobs were moving to the suburbs. Both Charlotte and Atlanta chose to build public housing on the edge of town, where there were minimal employment opportunities (Hanchett 1998; Bayor 1996). In some cities, the construction of densely populated public housing in existing black neighborhoods also led to overcrowded and/or segregated black schools. Schools in black neighborhoods in Atlanta with new public housing surpassed capacity (Bayor 1996). In the 1960s, Darius Swann, a black student in Charlotte, challenged the city’s school system for its role in maintaining segregated schools. Mr. Swann’s lawyer focused on the way that the city used zoning policies, public housing, and urban renewal to promote and maintain residential segregation (Bayor 1996). Despite long waitlists for public housing in major cities, the lack of access to jobs and high-quality schools likely made public housing less desirable to households who could afford private housing.

Changes in public housing quality

The decline in the quality of public housing projects over time also played a role in public housing’s growing reputation as housing of last resort. When public housing was first constructed, it offered a big improvement in housing quality for its tenants. Some tenants moved from slums without electricity, indoor plumbing, or enough beds. Public housing provided all of these amenities (Friedrichs 2011). An early tenant in St. Louis’s Pruitt-Igoe project described her apartment as a “poor man’s penthouse,” and tenants in Chicago’s Alteld Gardens described their new home as “paradise” (Friedrichs 2011, Hunt 2009).

Over time, however, the quality and nature of public housing changed. Low quality construction, as well as lack of maintenance due to inadequate funding, caused many of the buildings to deteriorate quickly. Arbitrary limits on construction costs per unit caused cities to take shortcuts during construction, which eventually led to elevated operating and maintenance costs (Goetz 2013). In 1958, Harrison Salisbury described New York City’s Fort Green public housing project in The New York Times, referring to “the broken windows, the missing light bulbs, the plaster cracking from the walls, the pilfered hardware, the cold drafty corridors, [and] the doors on sagging hinges …” (Salisbury 1958, 75). In St. Louis, the Housing Authority cut corners on the construction of the Pruitt-Igoe project by installing knobs that frequently broke on first use and inadequate window frames that allowed for window panes to be blown in by wind pressure (Meehan 1979). They also failed to properly insulate heated pipes or waterproof basement walls (Meehan 1979). By the early 1970s, the project had deteriorated so severely that the city demolished all 33 high-rises. While much of the decline in the physical structure of public housing was due to inadequate funding, many projects were subject to high volumes of vandalism, including broken light fixtures and windows, graffiti, and urination in elevators and stairwells. The high rates of vandalism and crime found in public housing have been blamed on the site design of projects, which led to a lack of defensible space and increased security and maintenance problems (Goetz 2013; Newman 1972).

Determinants of public housing intensity

Some previous research has studied correlates of public housing intensity. Note that the evidence in this literature is not directly applicable to our paper; this is because our sample includes 56 MSAs, whereas the studies we summarize below each use much larger samples of cities or counties.

Aiken and Alford (1970) investigate the characteristics of cities that adopted public housing, dividing characteristics into political culture, concentration of community power, centralization of formal political structure, community differentiation, and community integration. They proxy for political culture with median family income, the percent of children in private schools, and percent voting Democratic in 1964; for concentration of community power with percent high school graduates and percent of registered voters voting; for political structure with presence of a city-manager form of government, percent nonpartisan elections, and percent of city council elected at large; for community differentiation with age and size of the city; and for community integration with percent unemployed and percent migrant. Aiken and Alford also consider poverty measures, such as the percent of housing dilapidated in 1950, the percent of families with less than $3000 income in 1959, and the percent of the population that is nonwhite. They look at simple correlation coefficients between these controls and three measures of public housing implementation: the presence of any public housing, the number of years that it took a place to build their first public housing, and the amount of public housing per person. These correlations reveal that “older and larger cities, those with lower levels of education and income, fewer managers and officials, higher voting turnout and Democratic voting, a lower degree of in-migration, and higher unemployment levels have participated more in public housing” (p. 858). They also find that cities with higher levels of poverty and dilapidated housing are more likely to adopt public housing.

McDonald (2011) also examines the characteristics of cities that adopted public housing during this period. McDonald considers the characteristics of the population (e.g., population, percent nonwhite) as well as the private housing stock (e.g., age of housing stock, percent of owner-occupied units, percent of units with hot water). When he regresses public housing per capita on these characteristics, he finds that the percentage of low-income families and the percentage of nonwhite residents are positively correlated with public housing, while the percentage of old and owner-occupied housing is negatively correlated with public housing.

Shester (2011) also looks at the characteristics of places that adopted public housing. In her dissertation, she uses a sample of almost all counties in the U.S. and regresses 1970 public housing intensity on a wide variety of 1940 controls and state fixed effects. She finds that percent urban, population density, percent black, percent Democrat, and percent Catholic are all positively correlated with public housing. Percent of the labor force in manufacturing and agriculture, percent of owner-occupied units, median persons per rental unit, and median years of schooling are negatively correlated with public housing. Interestingly, even controlling for 16 county-level characteristics and state fixed effects, the R2 is only 0.4, suggesting that a great deal of unexplained, idiosyncratic variation remains.

Consistent MSA definitions

We limit our sample to individuals who lived in metropolitan statistical areas for which we could define consistent geographic boundaries over time. We used information from IPUMS on individuals’ reported state, county, and metropolitan area in 1950, and information on individuals’ state, county, metropolitan area, and county group in 1970. The 5% 1960 sample does not report county, metropolitan area, or county group, but reports public use micro-data areas (PUMAs). We were able to define consistent boundaries for 56 MSAs in 1950 and 1970 and were able to reconstruct identical boundaries in 1960 for 41 of these MSAs. For the remaining 15, we identified PUMAs that came as close as possible to our 1950 and 1970 consistent boundaries. To assess whether our results were dependent on our choice of 1960 boundaries, we defined two alternative sets of 1960 boundaries for these MSAs. First, we constructed a set of small boundaries, which included only PUMAs that lay completely inside of our consistent boundaries. In this scenario, our small boundaries did not include all of the area in the consistent boundaries but also did not include any area outside of these boundaries. There are three MSAs for which we cannot identify small boundaries. We then constructed a set of large boundaries, which included the entire area in our consistent boundaries as well as additional area in shared PUMAs. In most cases, our preferred boundaries are the small boundaries, as these are usually closer to the consistent ones. However, in some cases the larger ones are closer. For the three MSAs with no small boundaries, the large boundaries are used. In the table below, we list the county composition of our consistent definitions, the census’s MSA definitions in 1950, 1960, and 1970, and, when the 1960 boundaries are slightly different, our preferred, small, and large 1960 boundaries. Our results are virtually unaffected when we use these alternative MSA definitions.

Table 10 MSA county composition

Construction of fertility measure

Before 1970, the census did not ask never-married women about their fertility. To deal with this issue, IPUMS has created a series of rules that allows them to link likely mothers and children within a household. The census reports each individual’s placement in the household (PERNUM) and each individual’s relationship with the head of household (RELATE; e.g., spouse, child, child-in-law, parent, sibling, grandchild, other relative). IPUMS implements a set of rules (MOMRULE) that links women and children. For example, it links individuals listed as children of the head of household to women listed as the household head’s spouse, links the head and siblings of the head to women listed as the head’s mother, and links the head’s wife and siblings-in-law of the head to the head’s mother-in-law. IPUMS also links individuals who are grandchildren of the head of household to a daughter under the following condition:

“Persons listed as the grandchildren are linked to the most proximate preceding (on the form) ever-married daughter, unmarried daughter (if immediately followed by a grandchild), or daughter-in-law of the head, if the daughter/daughter-in-law is 11–59 years older than the grandchild. If no link is formed with a preceding female, the program looks for the most proximate subsequent female who satisfies the same criteria.”Footnote 26

IPUMS uses these rules to create the variable MOMLOC, which identifies the position of an individual’s mother in the household (if applicable), and to create the variable NCHILD, which indicates the number of children each woman has who are living in her household. This NCHILD variable is commonly used to answer questions about single motherhood before 1970 (e.g., Moehling 2007).

We received the new 5% 1960 sample from IPUMS before its official release date, and these imputed variables were not included. In order to make use of the 1960 data, we needed to construct the NCHILD variable for the 1960 data. We implemented the rules described above for our 1950, 1960, and 1970 samples. We compared our measures of mother and never-married single mother for 1950 using IPUMS’ NCHILD definition and our version of it and found remarkably similar results. The table below reports sample means for our mother and never-married single mother variables using both versions of NCHILD for the 1950 and 1970 samples. Our estimates for 1970 are slightly different because IPUMS uses information collected by the census on never-married women’s fertility (CHBORN) in that year, which is unavailable for never-married women in 1950 and 1960.

Table 11 Consistency of mother and never-married single mother variables using alternative measures of NCHILD.

We prefer our version, as it consistently measures motherhood and single motherhood using the same criteria in all years. Results are similar when using mother and never-married single mother measures defined using IPUMS’ NCHILD variable in 1950 and 1970 and our NCHILD measure for 1960.

Demographic characteristics of public housing residents

Our paper finds effects of public housing on single motherhood rates among black high school dropouts, but not among other race-education groups. Here, we show that it is not surprising that any effect of public housing is only detectable for black dropouts, since they are the group most likely to live in public housing.

We are not aware of data on public housing residents during our study period, but we have used the American Housing Survey (AHS) (United States Bureau of the Census 2016) to characterize the occupants of public housing for 1975–1977, soon after our sample period ends.

There are 22 MSAs that are in both the AHS and our census sample, and the results below are confined to these cities. Our results apply to the population of household heads. We use 1975–1977 because these are the first years in which we can observe both MSA identifiers and the education of the household head in the AHS data. (Education data was not collected for other household members until 1984.)

Table 12 and Fig. 3 show that black high school dropouts are greatly overrepresented in public housing. In Table 12, column 1 is the percentage of black dropouts in the MSA, and column 2 is the percentage of black dropouts among public housing residents in the MSA. The data in these columns are also plotted in Fig. 3. Column 3 is the ratio of the probability of living in public housing among black dropouts in the MSA to the probability of living in public housing among all other race-education groups in the MSA. Public housing is disproportionately composed of black high school dropouts; the median odds ratio is 8.1. Odds ratios for the other three race-education groups are reported in the final three columns of Table 12. Black high school graduates (median odds ratio = 3.4) and nonblack high school dropouts (median odds ratio = 1.5) are slightly overrepresented among public housing residents, but not nearly as severely as black dropouts.

Table 12 Demographic composition of public housing
Fig. 3
figure 3

Overrepresentation of black high school dropouts among public housing residents. Each dot represents one of the 22 MSAs that are in both our census sample and the American Housing Survey. See Table 12 for a list of MSAs and associated statistics. Estimates apply to the population of household heads in each MSA. Source: American Housing Survey, 1975–1977, Metropolitan Public Use Files

Effects of public housing on single motherhood by age

The results in the main text are for women ages 18–24. As a sensitivity check, we have re-estimated our preferred specification (specification 3) in Tables 3 and 4 for a variety of age ranges. In Tables 13 and 14, we report results from these specifications for ages 19–25, 20–26, 21–27, 22–28, and 23–29, as well as for ages 18–29, and for older women ages 25–34 and 35–44.

Table 13 Public housing intensity and single motherhood, by age (comparable to specification 3, Table 3)
Table 14 Public housing intensity and single motherhood, by age (comparable to specification 3, Table 4)

In Table 13 (comparable to Table 3), coefficients on public housing for nonblacks and black high school graduates are close to zero for all age bins, as in our main results for ages 18–24 in Table 3. For black high school dropouts, the coefficient is larger for ages 19–25, 20–26, and 21–27, ranging from 0.018 to 0.020, than for our main results for ages 18–24 (0.015). The point estimate is smaller for ages 22–28, 23–29, and 18–29.

The final two columns contain results for older women. The public housing coefficient is 0.0065 for ages 25–34 and 35–44. It is not surprising that the point estimates are smaller for older women because women must be never-married in our sample to be labeled a single mother. The percentage of the sample that has never been married drops sharply with age. For example, for the black 1970 sample, the percentage of never-married women decreases from 54% for ages 18–24, to 24% for ages 23–29, to 9% for ages 35–44.

When we allow for the coefficients to differ by year in Table 14 (comparable to Table 4), the public housing point estimate for black dropouts in 1970 is similar for ages 18–24, 19–25, 20–26, and 21–27, ranging from 0.023 to 0.025. The point estimate again falls for intervals that include older women. Our take on these results is that our findings are not sensitive to the age range that we focus on, but that the effect of public housing on single motherhood, defined as the percentage of women who are mothers and never-married, declines with age.

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Shester, K.L., Allen, S.K. & Handy, C. Concrete measures: the rise of public housing and changes in young single motherhood in the U.S.. J Popul Econ 32, 369–418 (2019). https://doi.org/10.1007/s00148-018-0704-1

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Keywords

  • Public housing
  • Single motherhood
  • Fertility
  • Marriage

JEL classification

  • I38
  • J13
  • N32